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AI-Assisted Antidiabetic Drug Consultation System for Glycemic Control in Type 2 Diabetes Patients Managed by Non-Specialist Physicians (AI-ADCS)

29. juni 2026 oppdatert av: National Taiwan University Hospital

Clinical Validation of AI-assisted Antidiabetic Drug Consultation System-1

This study tests whether an artificial intelligence (AI) tool can help doctors choose better diabetes medicines for their patients. Type 2 diabetes is very common, but there are far more patients than diabetes specialists, so many patients are treated by doctors who are not diabetes specialists. The researchers built an AI consultation system that gives doctors real-time suggestions and predictions about diabetes medicines while they are prescribing. The doctor always makes the final decision.

In this trial, patients with type 2 diabetes whose blood sugar is not well controlled will be placed by chance (randomly) into one of two groups. In one group, the doctor uses the AI system when deciding on diabetes medicines. In the other group, the doctor prescribes as usual, without the AI system. All medicines used are already approved in Taiwan and given at approved doses.

The study follows each patient for 12 months, with check-ups at the start and at 3, 6, 9, and 12 months. The main goal is to compare how much the patients' long-term blood sugar level (HbA1c) improves between the two groups after one year. The researchers also look at how many patients reach their blood sugar target, how often low blood sugar happens, and whether any side effects occur. The aim is to find out whether using the AI tool leads to better blood sugar control.

Studieoversikt

Studietype

Intervensjonell

Registrering (Antatt)

400

Fase

  • Ikke aktuelt

Kontakter og plasseringer

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Studiekontakt

Studer Kontakt Backup

Studiesteder

      • Taipei, Taiwan, 100
        • National Taiwan University Hospital
        • Ta kontakt med:

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

  • Voksen
  • Eldre voksen

Tar imot friske frivillige

Nei

Beskrivelse

Inclusion Criteria:

  • Adults aged 18 to 80 years
  • Diagnosis of type 2 diabetes for at least 6 months
  • HbA1c above 8% within the past 3 months
  • Currently using one or more oral antidiabetic drugs
  • Able to understand and provide written informed consent

Exclusion Criteria:

  • Pregnancy or breastfeeding
  • Recent participation in another interventional clinical trial
  • Cognitive impairment precluding understanding of the study
  • Active cancer treatment within the past 6 years
  • Use of systemic steroids

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

  • Primært formål: Behandling
  • Tildeling: Randomisert
  • Intervensjonsmodell: Parallell tildeling
  • Masking: Enkelt

Våpen og intervensjoner

Deltakergruppe / Arm
Intervensjon / Behandling
Eksperimentell: AI-Assisted Prescribing
Non-specialist physicians prescribe antidiabetic medications after consulting the AI-assisted antidiabetic drug consultation system. The system provides real-time, interactive prescribing recommendations, a drug-prioritization order, and outcome predictions. The physician retains full control over the final prescribing decision. All medications are approved in Taiwan and prescribed within approved dose ranges. Patients are followed for 12 months.
A machine-learning based clinical decision support software that provides non-specialist physicians with real-time, interactive antidiabetic prescribing recommendations, a drug-prioritization order, and outcome predictions (e.g., the predicted likelihood of reaching glycemic targets and responder/non-responder status for individual drugs). The system was developed and validated using the NTUH integrated medical database platform. It provides advisory recommendations only; the treating physician retains full control over the final prescribing decision. All recommended medications are approved in Taiwan and within approved dose ranges.
Aktiv komparator: Manual Prescribing (Non-AI)
Non-specialist physicians prescribe antidiabetic medications manually according to usual clinical practice, without using the AI consultation system. All medications are approved in Taiwan and prescribed within approved dose ranges. Patients are followed for 12 months.
Antidiabetic medications prescribed manually by non-specialist physicians according to usual clinical practice, without using the AI consultation system. All medications are approved in Taiwan and prescribed within approved dose ranges.

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Change in HbA1c from baseline to 12 months
Tidsramme: Baseline and 12 months
The between-group difference in the change in glycated hemoglobin (HbA1c) from baseline to 12 months, comparing the AI-assisted prescribing arm with the manual prescribing (control) arm. HbA1c reflects long-term glycemic control. The primary analysis uses analysis of covariance (ANCOVA) adjusting for baseline HbA1c, following the intention-to-treat principle.
Baseline and 12 months

Sekundære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Proportion of participants achieving HbA1c < 7.0% at 12 months
Tidsramme: 12 months
The proportion of participants reaching the glycemic target of HbA1c below 7.0% at 12 months, compared between arms using chi-square tests.
12 months
Incidence of hypoglycemia over 12 months
Tidsramme: Up to 12 months
Incidence of hypoglycemic events over the 12-month follow-up, graded by severity: Level 1, glucose < 70 mg/dL (3.9 mmol/L) and ≥ 54 mg/dL (3.0 mmol/L); Level 2, glucose < 54 mg/dL (3.0 mmol/L); Level 3, severe hypoglycemia requiring assistance of another person regardless of glucose value. Compared between arms using Poisson regression.
Up to 12 months
Incidence of prespecified adverse events over 12 months
Tidsramme: Up to 12 months
Incidence of prespecified adverse events over the 12-month follow-up, including urinary tract infection, lower-limb edema, signs of heart failure, fractures, nausea, vomiting, and diarrhea. Compared between arms using Poisson regression.
Up to 12 months
Change in HbA1c from baseline at 3, 6, 9, and 12 months
Tidsramme: Baseline, 3, 6, 9, and 12 months
Baseline, 3, 6, 9, and 12 months

Samarbeidspartnere og etterforskere

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Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Antatt)

1. juli 2026

Primær fullføring (Antatt)

1. november 2027

Studiet fullført (Antatt)

1. november 2027

Datoer for studieregistrering

Først innsendt

29. juni 2026

Først innsendt som oppfylte QC-kriteriene

29. juni 2026

Først lagt ut (Faktiske)

6. juli 2026

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

6. juli 2026

Siste oppdatering sendt inn som oppfylte QC-kriteriene

29. juni 2026

Sist bekreftet

1. juni 2026

Mer informasjon

Begreper knyttet til denne studien

Andre studie-ID-numre

  • 202507154RINA
  • 115-X007 (Annet stipend/finansieringsnummer: National Taiwan University Hospital Yunlin Branch)

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